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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,341 papers · 148 categories

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70141211281 · Jun 202019922001200920182026
48 results for fluctuating objects

Stochastic gradient descent's long-term fluctuations are described by a diffusion limit.

problem Long-term behavior of stochastic gradient descent in non-smooth settings.
method Functional central limit theorem applied to rescaled trajectory of SGD.
result Characterization of long-term fluctuations around the minimizer.

Study uses neural networks to predict wall quantities in turbulent flows.

problem Predicting wall quantities in turbulent open channel flows.
method Training convolutional neural networks (FCN) and a proposed R-Net architecture to predict wall-shear-stress and wall pressure.
result R-Net architecture performs better and predicts wall quantities with around 10% error.

Deep learning detects sleep state fluctuations in neonates from single EEG channel.

problem Monitoring sleep state fluctuations in neonatal intensive care units.
method Deep learning-based algorithm trained on 53 EEG recordings, validated on 30 polysomnography recordings.
result High accuracy (90%) in detecting quiet sleep states from single EEG channel, generalizing well to external dataset.

The paper finds optimal threshold strategies for insurance companies with a positive terminal value at creeping ruin.

problem Optimizing dividend payments in an insurance company's surplus process with a positive terminal value at creeping ruin.
method Using fluctuation theory, the paper derives explicit formulas for the objective function and shows the optimality of threshold strategies.
result Threshold strategies are optimal for the dividend optimization problem under certain conditions.

Bayesian neural networks explore rare fluctuations for better feature learning.

problem Understanding rare but dominant fluctuations in Bayesian neural networks.
method Large-deviation theory and joint optimization over predictors and internal kernels.
result Posterior rate function optimization reveals data-dependent kernel selection.

Study shows cryptocurrency price fluctuations become more similar to national currencies over time.

problem Understanding the volatility and inequality in cryptocurrency prices.
method Calculated inequality measures (Gini, Kolkata indices, QQ factor) for cryptocurrency and national currency price fluctuations over 10 years.
result Cryptocurrency price fluctuations become more similar to national currencies over time.

Bayesian models' singular fluctuation is shown to be akin to specific heat, influencing model complexity and generalization.

problem Understanding the thermodynamic interpretation of singular fluctuation in Bayesian models.
method Showed singular fluctuation as the curvature of Bayesian free energy and variance of log-likelihood observable under a Gibbs posterior.
result Singular fluctuation is the statistical analogue of specific heat, controlling model complexity and generalization.

This paper addresses robust CBs for linear SEMs with model fluctuations.

problem Designing interventions in causal systems with linear SEMs that are robust to model fluctuations.
method Develops a robust CB algorithm and analyzes its regret under model deviation.
result The proposed algorithm achieves nearly optimal ildeO(T) ilde{\mathcal{O}}(\sqrt{T}) regret when CC is o(T)o(\sqrt{T}) and maintains sub-linear regret for a broader range of CC.

New portfolio optimization method considers both asset-specific and systemic risks for financial networks.

problem Optimizing portfolios with both idiosyncratic and systemic risks in financial networks.
method Developed a multi-objective optimization model that incorporates idiosyncratic variance and network clustering coefficient.
result Optimal portfolios outperform in terms of return measures and have less drawdown compared to traditional strategies.

We study the nature of fluctuations in variety of price indices involving companies listed on the New York Stock Exchange. The fluctuations at multiple scales are extracted through the use of wavelets belonging to Daubechies basis. The fact that these basis sets satisfy vanishing moments conditions makes them ideal to …

2012-05-08abs ↗pdf ↗

New spectral functionals for Dirac operators with inner fluctuations computed.

problem Spectral functionals and Dirac operators with inner fluctuations.
method Extension of spectral functionals for Dirac operators with inner fluctuations.
result Computed spectral Einstein functional for Dirac operator with inner fluctuations on even-dimensional spin manifolds.

We propose a new approach for properly analyzing stochastic time series by mapping the dynamics of time series fluctuations onto a suitable nonequilibrium surface-growth problem. In this framework, the fluctuation sampling time interval plays the role of time variable, whereas the physical time is treated as the analog…

2008-08-24abs ↗pdf ↗

Derives fluctuation theorems and thermodynamic uncertainty relations for systems modeled as Bayes nets.

problem Entropy production in interacting systems modeled as Bayes nets.
method Derives fluctuation theorems and thermodynamic uncertainty relations for arbitrary sets and conditioned sets of systems in Bayes nets.
result Relates the entropy production of the overall system to the precisions of probability currents in individual systems.

This work studies fluctuation in multilayer neural networks using mean field theory.

problem Understanding fluctuation in multilayer neural networks with mean field training.
method Developed a second-order mean field limit to capture fluctuation, demonstrating stability of gradient descent training.
result Gradient descent training in multilayer networks biases towards minimal fluctuation, even after convergence.

We propose a new approach for analyzing price fluctuations in their strongly correlated regime ranging from minutes to months. This is done by employing a self-similarity assumption for the magnitude of coarse-grained price fluctuation or volatility. The existence of a Cramer function, the characteristic function for s…

2001-01-12abs ↗pdf ↗

We analyze daily prices of 29 commodities and 2449 stocks, each over a period of 15\approx 15 years. We find that the price fluctuations for commodities have a significantly broader multifractal spectrum than for stocks. We also propose that multifractal properties of both stocks and commodities can be attributed mainl…

2003-08-01abs ↗pdf ↗

Study identifies contagion in aggregated defaults despite environmental changes.

problem Identify contagion in aggregated default counts with fluctuating probabilities.
method Compare three contagion mechanisms (Davis-Lo, Torri, Vasicek) under i.i.d. and hierarchical specifications.
result Threshold contagion is largely absorbed into environmental heterogeneity, while cumulative contagion leaves a persistent signature.

We address the question of how stock prices respond to changes in demand. We quantify the relations between price change GG over a time interval ΔtΔt and two different measures of demand fluctuations: (a) ΦΦ, defined as the difference between the number of buyer-initiated and seller-initiated trades, and (b) ΩΩ, def…

2001-06-29abs ↗pdf ↗

Study on price fluctuations in NFT market, showing heavy-tailed distributions and long-range memory.

problem Characterizing price fluctuations in NFT market.
method Analysis of capitalization, floor price, transactions, inter-transaction times, and volume value of NFTs.
result NFT market exhibits heavy-tailed probability distribution functions, well described by stretched exponentials, with long-range memory.

Stock market price fluctuations follow Lévy's stable distribution over long term.

problem Understanding the stability of stock market price fluctuations over different time scales.
method Estimated Lévy's stable parameters from four stock markets over long and short term.
result Stable parameters from different stock markets showed a unique value over long term, but fluctuated with correlation in short term.

Spectral clustering performance depends on eigenvector fluctuations, shown to be Gaussian.

problem Predicting the performance of spectral clustering.
method General spike random matrix model and rotational invariance of noise.
result Fluctuations of eigenvector entries are Gaussian in large-dimensional regime.

We analyze the fluctuation of the loss from default around its large portfolio limit in a class of reduced-form models of correlated firm-by-firm default timing. We prove a weak convergence result for the fluctuation process and use it for developing a conditionally Gaussian approximation to the loss distribution. Nume…

2013-04-04abs ↗pdf ↗

Derives scaling limits and fluctuations for SGD in high dimensions.

problem Understanding SGD behavior in high-dimensional settings with varying noise levels.
method Interacting particle system approach, treating SGD iterates as such, with covariance structure considered.
result Precise three-step phase transition observed in SGD behavior: ballistic, diffusive, then random.

Study analyzes fluctuations in Mexican financial market index.

problem Understanding intra-day fluctuations in Mexican financial market index.
method Statistical analysis of high frequency tick-to-tick data, temporal aggregation, and comparison of distributions.
result Intra-day fluctuations do not follow alpha-stable distributions, suggesting autocorrelations.

New approach models fluctuating asset correlations for better credit risk assessment.

problem Modeling fluctuating asset correlations for accurate credit risk assessment.
method Ensemble approach with fluctuating asset correlations, reducing parameters to two.
result Validated approach with Monte-Carlo simulations for Value at Risk and Expected Tail Loss.

We constructed an analog electrical circuit which generates fluctuations in which probability density function has power law tails. In the circuit fluctuations with an arbitrary exponent of the power law can be obtained by adjusting the resistance. With this low cost circuit the random fluctuations which have the simil…

2001-04-18abs ↗pdf ↗

The financial market and turbulence have been broadly compared on account of the same quantitative methods and several common stylized facts they shared. In this paper, the She-Leveque (SL) hierarchy, proposed to explain the anomalous scaling exponents deviated from Kolmogorov monofractal scaling of the velocity fluctu…

2012-09-19abs ↗pdf ↗

This paper proposes a framework to predict long-term trends and short-term fluctuations in multivariate time series.

problem Existing prediction methods often ignore the distinction between long-term trends and short-term fluctuations.
method The paper introduces a MTS forecasting framework that uses both original time series and its first difference to capture long-term trends and short-term fluctuations.
result The proposed method improves forecasting performance by using more supervision information.

Predicting absolute magnitude of fluctuations of price, even if their sign remains unknown, is important for risk analysis and for option prices. In the present work, we display our predictions about absolute magnitude of daily fluctuations of the Dow Jones Industrials Average (DJIA), utilizing the original theory of c…

2006-02-08abs ↗pdf ↗

The paper analyzes fluctuations in ensemble models in high-dimensional settings.

problem Understanding statistical fluctuations in ensemble models in high-dimensional settings.
method Develops a rigorous theory for the study of fluctuations in ensemble of generalised linear models.
result Provides a complete description of the asymptotic joint distribution of the empirical risk minimizer for convex losses in high-dimensional settings.

We investigate the large-fluctuation dynamics in financial markets, based on the minute-to-minute and daily data of the Chinese Indices and German DAX. The dynamic relaxation both before and after the large fluctuations is characterized by a power law, and the exponents p±p_\pm usually vary with the strength of the lar…

2013-08-03abs ↗pdf ↗

In this paper, we present own point of view how the unexpected fluctuations of the long-term real interest rate can be explained. We describe a macroeconomic environment by the modification of the fundamental macroeconomic equilibrium model called the IS-LM model. Last but not least, we suggest a possible cooperation b…

2012-11-12abs ↗pdf ↗

The study reveals the hierarchical structure of the international FOREX market using currency fluctuation distribution similarities.

problem Understanding the hierarchical structure of the international FOREX market.
method Using Jensen-Shannon divergence to quantify the similarity between normalized logarithmic return distributions of currencies.
result Clusters of currencies are consistent with the nature of underlying economies but diverge during crises.

Copulas reveal strong positive dependencies in stock demand fluctuations due to volume imbalances.

problem Analyzing dependencies of stock demands using local volume fluctuations.
method Copula analysis of empirical data to model dependence structures.
result Large local fluctuations of signed traded volumes increase positive dependencies in demand but slightly lower negative ones.

We study the cause of large fluctuations in prices in the London Stock Exchange. This is done at the microscopic level of individual events, where an event is the placement or cancellation of an order to buy or sell. We show that price fluctuations caused by individual market orders are essentially independent of the v…

2003-12-30abs ↗pdf ↗

The study analyzes neural interactions using an Ising model to reveal contributions of pairwise interactions to sparseness and fluctuation.

problem Understanding the contributions of pairwise interactions to sparseness and fluctuation in neural activity.
method Inference methods for a time-dependent Ising model to analyze neural interactions and estimate time-dependent neural interactions with credible intervals.
result Pairwise interactions contribute to increasing sparseness and fluctuation in neural activity.

Model shows how heterogeneity in strategies and risk tolerance affects financial market stability.

problem Understanding how heterogeneity impacts financial market dynamics.
method Agent-based model incorporating heterogeneous investment strategies and risk tolerance.
result Heterogeneity in strategies and risk tolerance suppresses price fluctuations.